8th Summer Institute in Statistics for Clinical and Epidemiological Research (SISCER)


This module is currently full. Registrations are closed at this time.

Module 10: Generalized Estimating Equations for Longitudinal Data Analysis

Mon, July 19
Registration for this module closes July 12. 

 

Live sessions will be held 8:30 a.m. - noon Pacific (11:30-3 p.m. Eastern).

Longitudinal studies follow individuals over time and repeatedly measure health status, which facilitates prospective ascertainment of exposures and incident outcomes, and identification of changes over time within individuals. Analyses of longitudinal data must account for the correlation that arises from collecting repeated measures on the same individuals over time.

This module will introduce statistical methods for the analysis of longitudinal data, with a focus on marginal (or, population-averaged) models fit via generalized estimating equations. Relevant theoretical background will be provided. An illustrative example (conducted in R) will be used to illustrate analysis approaches, modeling strategies, and interpretation of results.

This course is targeted toward individuals with little or no prior experience with statistical methods for longitudinal data analysis. Experience with using regression methods to analyze data (e.g., linear regression, logistic regression) is important background for this module.